PURPOSE. To
describe the reproducibility of competitive performance of elite
track-and-field athletes and to derive the smallest worthwhile enhancements
of performance in these events.METHODS. The data were official results of events in 17 competitions
of an annual series of the International Amateur Athletic Federation
extending over 101 d.Typical
within-athlete variability from competition to competition was derived as a
coefficient of variation by repeated-measures analysis of log-transformed
times (for running and hurdling events) or distances (for jumping and
throwing events).The smallest worthwhile
performance enhancement was taken as half the within-athlete variability.RESULTS and DISCUSSION. Within-athlete
variabilities were as follows: running and hurdling events up to 1500 m,
1.0%; longer runs and steeplechase, 1.4%; triple and high jump, 1.7%; pole
vault and long jump, 2.4%; discus, javelin, and shot put, 2.8% (90%
confidence limits all ~Χ/χ1.13).The differences between events presumably reflect differing
contributions of energy systems, pacing strategies, wind resistance and
skill.Females may have had a little
more variability in performance (~1.1Χ) than males in
some events, possibly because of less depth of competition.There was some evidence that variability
increased with increasing time between competitions for the short running
events (from ~0.7% for ~1 wk to ~1.1% for ~100 d).The top-half athletes in each event were
less variable than the bottom-half in running and hurdling up to 1500 m
(0.8 vs 1.1%) and in longer runs and steeplechase (1.1 vs 1.6%), but
differences were unclear in the other events. A likely explanation is less
consistent motivation in endurance athletes who were not in the medal stakes.
CONCLUSIONS. Coaches and sport scientists should focus on enhancements of
as little as 0.3-0.5% for elite track athletes through 0.9-1.5% for elite
field athletes.

This paper is the latest in a series
aimed at estimating the smallest worthwhile change in performance for
athletes who compete as individuals in sports where the outcome is determined
by a single score, such as a time or distance.The smallest worthwhile change in performance
is important when assessing athletes with a performance test to make
decisions about meaningful changes in an individual or to research strategies
that might affect performance (Hopkins, 2004). An
estimate of the smallest change comes from an analysis of reliability
(reproducibility or variability) of competitive performancethe smallest
change is in fact about half the typical variation a top athlete shows from
competition to competition (Hopkins et al., 1999).

The previous published studies on
variability of competitive performance and smallest changes have been for
junior swimmers (Stewart and Hopkins, 2000), elite swimmers (Pyne et al., 2004),
non-elite runners (Hopkins and Hewson, 2001), and triathletes (Paton and Hopkins, 2005). The present study of track-and-field athletes is based on data
that I acquired and analyzed some years ago and that I have referred to in
various publications.

Official
result times of the 1997 Grand Prix series of international competitions were
obtained from the website of the International Amateur Athletic Federation.
The series consisted of 18 different kinds of track-and-field events staged
at 17 mainly European venues over 101 days. An event at a venue was included
in the analysis of reliability for that kind of event if it included at least
2 athletes who had entered the same event at other venues.The men's high jump provided the least
amount of data:8 athlete-entries for
3 athletes at 3 venues; at the other extreme, the men's 110-m hurdle provided
120 athlete-entries for 20 athletes at 17 venues.A typical women's event in the analysis was
the javelin, which provided 48 athlete-entries for 12 athletes at 7
venues.There were insufficient data
for the analysis of hammer throw, women's long jump and women's pole vault.

The
analyses were similar to those used in the study of triathlete performance in
this issue (Paton and Hopkins, 2005).Briefly, I used mixed modeling of
log-transformed times to derive an athlete's typical percent variation in performance
from competition to competition as a coefficient of variation.I performed separate analyses for males and
females in each event, and for the top and bottom half of athletes in each
event.Differences between
coefficients of variation were considered substantial if their ratio was
greater than 1.10.

I also
analyzed for the effect of time on variability estimated between all pairs of
competitions for both sexes combined but for shorter (100- to 1500-m) and
longer (3000- to 10,000-m) running events separately.I corrected the small bias in the
individual estimates of coefficients of variation by multiplying by
1+1/(4DF), where DF=degrees of freedom (Gurland and Tripathi, 1971).I then fit quadratics to the log-log plots
and used 1000 bootstrapped samples to derive confidence limits for the
quadratics and for comparisons (ratios) of the coefficients of variation for
different times between competitions.

Table
1 shows the typical within-athlete variation in performance from competition
to competition for the various events. I have not systematically derived confidence
limits for a comparison of the variability in the different types of event,
but it is reasonably clear from the confidence limits for each type that
athletes in longer running events are more variable their performance than
those in the shorter events, that athletes in the throwing events are about
twice as variable, and that athletes in the high jump and triple jump are somewhere
in between.

Table 1.
Typical variability of a track-and-field athlete's performance between
international competitions, expressed as a coefficient of variation (CV).

Event

CV (%) (90% conf. limits)

Running
<3 kma

1.0
(0.91.1)

Running 3-10
kmb

1.4
(1.21.6)

High jump,
triple jump

1.7
(1.51.9)

Long jump,
pole vault

2.4
(2.12.7)

Discus,
javelin, shot put

2.8
(2.43.2)

a100- to 1500-m runs; 100- to 400-m hurdles.

b1500- to 10,000-m runs; male 3000-m steeplechase.

The higher reliability of the shorter
running and hurdling events may be due to differing contributions of energy
systems, pacing strategies, and wind resistance relative to the longer
events.Contributions of energy
systems and skill may explain the lower reliability of field events and differences
between the field events.The
differences between variability of performance in the different types of
event mirrors those in performance tests in these modes of exercise (Hopkins et al., 2001), although the variability in
these competitions is generally a little less than that for athletes in the
best tests.

Table 2 shows the variability in
performance for females and males in the events where there were sufficient
comparable data.Given the uncertainty
in the estimates of variability, females were probably more variable than
males by a trivial-small factor of ~1.1 (about 10%) overall, but there may be
greater or smaller differences in specific events.The difference may be due to less depth of
competition for the females rather than differences in physiology.

Table 2.Variability of performance of female and male
track-and-field athletes expressed as coefficients of variation (CV).Comparison of variabilities is shown as
ratio of female/male.

The estimates
of athlete variability in running and hurdling events for all pairwise
combinations of competitions are shown in Figure 1.Much of the scatter in the points is due to
sampling variation arising from the small sample size for the pairwise
combinations, as can be seen from the expected sampling variation for a
typical point.

Figure 1. Typical variation in an
athlete's performance between all pairs of competitions for the short
running and hurdling events (< 3 km) and the long running events (3-10
km), plotted against time between the competitions. Bars are standard
deviations representing typical sampling variation for a true variation of
1% with the average sample size of the points (6 athletes).Curves are quadratics, with 90%
confidence limits.

Athlete
variability for short runs was minimum (0.7%) at around 1 wk between
competitions and greatest at 100 d (1.1%).The trend towards more variability with increasing time between competitions
was clear: for example, the ratio of variability at 64 d to that at 8 d was
1.40 (90% confidence limits 1.161.65). The quadratic model probably
overestimates the trend for longer times, because a plateau is evident in the
plot beyond ~50 d. A small increase in variability due to variation in training
and health over a period of weeks is not unexpected, but over more than
several months these athletes, like elite triathletes (Paton and Hopkins, 2005), probably maintain their
ability to perform.

Variability
for the long runs was also a minimum (1.0%) around 1 wk between competitions
for this sample.However, confidence
limits were too wide to allow conclusions about any substantial trend; for
example, the ratio of 100-d to 8-d variability was 1.16 (0.771.69).

Effect of Caliber of
Athlete

Table 3 shows that the athletes in the top half of the field were
clearly less variable in the running events.Others have found similar results with running and swimming and
cycling and have attributed it to better pacing, more consistent preparation,
or more consistent motivation on the part of the very best athletes (Hopkins and Hewson, 2001; Stewart and Hopkins, 2001; Pyne et al.,
2004; Paton and Hopkins, 2005). I
favor the last of these possible explanations for endurance athletes: an
athlete who realizes early on that s/he is not in the medal stakes must
surely sometimes put less effort into the rest of the race.The situation is less clear in the field
events, owing to the uncertainty in the estimates.More data are required before one seeks
explanations for what may be more variability with top-half athletes in the
throwing events.

Conclusions

The main purpose of this study was to
obtain estimates of the smallest worthwhile change in performance for elite
athletes in each of the track-and-field events.Halving the variability of performance of
the best athletes in each event provides such estimates.Coaches and sport scientists should
therefore focus on enhancements of as little as 0.3-0.5% for elite track
athletes through 0.9-1.5% for elite field athletes.